Robust Parallel Machine Scheduling Problem with Uncertainties and Sequence-Dependent Setup Time

A parallel machine scheduling problem in plastic production is studied in this paper. In this problem, the processing time and arrival time are uncertain but lie in their respective intervals. In addition, each job must be processed together with a mold while jobs which belong to one family can shar...

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Main Authors: Hongtao Hu, K. K. H. Ng, Yichen Qin
Format: Article
Language:English
Published: Hindawi Limited 2016-01-01
Series:Scientific Programming
Online Access:http://dx.doi.org/10.1155/2016/5127253
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spelling doaj-b3ed4d7c20b2415fb4ad95cf6aa120572021-07-02T03:41:28ZengHindawi LimitedScientific Programming1058-92441875-919X2016-01-01201610.1155/2016/51272535127253Robust Parallel Machine Scheduling Problem with Uncertainties and Sequence-Dependent Setup TimeHongtao Hu0K. K. H. Ng1Yichen Qin2Logistics Engineering College, Shanghai Maritime University, Shanghai, ChinaDepartment of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong KongDepartment of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong KongA parallel machine scheduling problem in plastic production is studied in this paper. In this problem, the processing time and arrival time are uncertain but lie in their respective intervals. In addition, each job must be processed together with a mold while jobs which belong to one family can share the same mold. Therefore, time changing mold is required for two consecutive jobs that belong to different families, which is known as sequence-dependent setup time. This paper aims to identify a robust schedule by min–max regret criterion. It is proved that the scenario incurring maximal regret for each feasible solution lies in finite extreme scenarios. A mixed integer linear programming formulation and an exact algorithm are proposed to solve the problem. Moreover, a modified artificial bee colony algorithm is developed to solve large-scale problems. The performance of the presented algorithm is evaluated through extensive computational experiments and the results show that the proposed algorithm surpasses the exact method in terms of objective value and computational time.http://dx.doi.org/10.1155/2016/5127253
collection DOAJ
language English
format Article
sources DOAJ
author Hongtao Hu
K. K. H. Ng
Yichen Qin
spellingShingle Hongtao Hu
K. K. H. Ng
Yichen Qin
Robust Parallel Machine Scheduling Problem with Uncertainties and Sequence-Dependent Setup Time
Scientific Programming
author_facet Hongtao Hu
K. K. H. Ng
Yichen Qin
author_sort Hongtao Hu
title Robust Parallel Machine Scheduling Problem with Uncertainties and Sequence-Dependent Setup Time
title_short Robust Parallel Machine Scheduling Problem with Uncertainties and Sequence-Dependent Setup Time
title_full Robust Parallel Machine Scheduling Problem with Uncertainties and Sequence-Dependent Setup Time
title_fullStr Robust Parallel Machine Scheduling Problem with Uncertainties and Sequence-Dependent Setup Time
title_full_unstemmed Robust Parallel Machine Scheduling Problem with Uncertainties and Sequence-Dependent Setup Time
title_sort robust parallel machine scheduling problem with uncertainties and sequence-dependent setup time
publisher Hindawi Limited
series Scientific Programming
issn 1058-9244
1875-919X
publishDate 2016-01-01
description A parallel machine scheduling problem in plastic production is studied in this paper. In this problem, the processing time and arrival time are uncertain but lie in their respective intervals. In addition, each job must be processed together with a mold while jobs which belong to one family can share the same mold. Therefore, time changing mold is required for two consecutive jobs that belong to different families, which is known as sequence-dependent setup time. This paper aims to identify a robust schedule by min–max regret criterion. It is proved that the scenario incurring maximal regret for each feasible solution lies in finite extreme scenarios. A mixed integer linear programming formulation and an exact algorithm are proposed to solve the problem. Moreover, a modified artificial bee colony algorithm is developed to solve large-scale problems. The performance of the presented algorithm is evaluated through extensive computational experiments and the results show that the proposed algorithm surpasses the exact method in terms of objective value and computational time.
url http://dx.doi.org/10.1155/2016/5127253
work_keys_str_mv AT hongtaohu robustparallelmachineschedulingproblemwithuncertaintiesandsequencedependentsetuptime
AT kkhng robustparallelmachineschedulingproblemwithuncertaintiesandsequencedependentsetuptime
AT yichenqin robustparallelmachineschedulingproblemwithuncertaintiesandsequencedependentsetuptime
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